A comprehensive Python library for downloading Midcontinent Independent System Operator (MISO) public reports into pandas dataframes.
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Updated
Mar 8, 2025 - Python
A comprehensive Python library for downloading Midcontinent Independent System Operator (MISO) public reports into pandas dataframes.
Machine learning and regression models for day-ahead and balancing market trading of wind power using real-world data from Bornholm wind farms.
Forecasts of the power market prices before the day-ahead market closure time are prone to significant error. I predict whether the day ahead (PTF in Turkish) or balancing (standard marginal price (SMF in Turkish)) will be higher at a given hour next day. It creates decisive forecasts for reducing the balancing cost.
This program optimizes the operation and bidding strategy of renewable-based Virtual Power Plants (RVPPs) under different sources of uncertainty using MILP-based flexible robust optimization approaches. The model considers RVPP participation in the Day-Ahead, Secondary Reserve, and Intra-Day Iberian electricity markets.
Case study results for the paper "Moving from linear to conic markets for electricity"
Co-optimization framework for Battery Energy Storage Systems between day-ahead energy arbitrage and balancing reserves. Builds a unified optimization model and evaluates revenue of multiple strategies using French market data (RTE/Ember).
Battery sizing under dispatch fidelity and imbalance-penalty regimes (DK1 + ERCOT, 2021-2023)
End-to-end forecasting pipeline for Turkish Day-Ahead electricity prices. Demonstrates time-series feature engineering and proper rolling-window backtesting.
ERCOT BESS arbitrage: LightGBM dispatch adds +$2.6M/yr (100 MW battery) over persistence on 2-year held-out test (77% of ceiling).
Day-Ahead Market (DAM) electricity price forecasting engine using XGBoost on Indian Energy Exchange (IEX) data.
Day-ahead GB electricity price forecasting: weather → renewables → price pipeline with ML and deep learning (BENV0148 UCL)
Risk-adjusted 10-year TCO framework for hyperscale data center siting (5 U.S. markets) — combines AEO + Cambium forward prices, calibrated XGBoost stress events, Monte Carlo NPV with CVaR-95, and 6-case rank-robustness sensitivity.
SQL analytical toolkit for Turkish electricity market data. Demonstrates window functions, CTEs, rolling aggregates — DuckDB + Python + Jupyter.
Interactive map dashboard visualizing redispatch data for Germany, 2024
Downloading and storing the TenneT aFRR bid ladders at regular intervals
Real-time LMP price forecasting dashboard for Nine Mile Point nuclear node — PJM Data Miner API, SQLite, scikit-learn, Streamlit
ML pipeline for predicting Romanian grid imbalance and capturing intraday/imbalance arbitrage spread
Causal ML for Swiss aFRR price spike prediction — German wind forecast errors → unplanned loop flows → balancing cost spikes. XGBoost + SHAP + MLflow + Databricks + Airflow pipeline with PSI drift monitoring and champion/challenger retraining.
Near-Orthogonal Regimes in ISO New England: Price Level and Temporal Persistence as Non-Redundant Dimensions
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